Abstract PO-049: The neural landscape is associated with functional outcomes for patients with oropharyngeal squamous cell carcinoma
Bibliographic record
Abstract
Abstract Despite the excellent prognosis of patients with oropharyngeal squamous cell carcinoma (OPSCC), long-term functional impairment (e.g., dysphagia) is a major burden for many patients. Recent studies have explored the role of pharyngeal constrictors and muscle fibrosis in dysphagia. However, to date, no study has examined the association between the OPSCC neural microenvironment and posttreatment functional impairment. We hypothesized that cancer-related neuronal changes in the OPSCC tumor microenvironment (TME) would affect patients’ prognoses. Therefore, in the present study, we investigated whether cancer-related changes in the tumor neuronal microenvironment influence functional outcomes in patients with OPSCC. Prospectively collected, patient-reported outcomes (i.e., from the MD Anderson Symptom Inventory [MDASI] and the MD Anderson Dysphagia Inventory [MDADI]) and functional outcomes from the Dynamic Imaging Grade of Swallowing Toxicity [DIGEST] for patients with OPSCC were collected (n=29). OPSCC tissue samples were obtained from surgically treated patients, and multiplex/high-plex immunofluorescence and machine learning techniques were used to correlate neuronal changes with prospectively collected patient data. Electromyography was performed to assess the neuronal populations involved in neuropathies after treatment. A murine animal model of dysphagia was also used to correlate the neuronal changes. The results showed that sensory nerves with adrenergic features (CGRP+TH+) were associated with perineural and lymphovascular invasion. In addition, we found that human papillomavirus associated OPSCC was associated with an enrichment of parasympathetic progenitors (VIP+DCX+). Poor MDASI scores were associated with CGRP+, adrenergic (TH+), or CGRP+TH+ innervation, and growing progenitor neurons (GAP43+DCX+) were associated with improved oral symptoms. Swallowing, measured by MDADI scale revealed that patients with tumors enriched with growing (GAP43+), parasympathetic (VIP+), and neuronal progenitor (DCX+) neurons reported poor swallowing perception; subgroup electromyography analysis confirmed our findings. Quantitative swallowing assessment with DIGEST by speech language pathologists revealed that TMEs innervated by CGRP+, TH+, and MBP+ neurons were associated with poor swallowing functions. Finally, using a murine model of dysphagia we confirmed that sensory (CGRP+), myelinated (MBP+), and cholinergic parasympathetic (CHAT+) or progenitor (CHAT+DCX+) enrichment was associated with denervation and downstream dysphagia. In conclusion, our results show that neuronal changes are correlated with clinical features in OPSCC patients. Patients’ functional outcomes after therapy completion are influenced by distinct nerve populations in the TME. These benchmark data should be further evaluated as a potential target for cancer survivors with dysphagia and as a biomarker for patients who might need escalated swallowing rehabilitation during and after treatment for OPSCC. Citation Format: Shajedul Islam, Frederico O. Gleber-Netto, Collin F. Mulcahy, Mica D. E. Glaun, Patrick J. Hunt, Michelle D. Williams, Carly E. Barbon, Weilu Zhao, Adewale Adebayo, Shamima Akhter, Tongxin Xie, Ismail Yaman, Jared K. Burks, Javier Gomez, Karin Woodman, Teresa E. Lever, Katherine A. Hutcheson, Moran Amit. The neural landscape is associated with functional outcomes for patients with oropharyngeal squamous cell carcinoma [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-049.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".